Staff/Senior Machine Learning Research Engineer (AI)

Location: San Francisco, CA; New York, NY. The stated salary range also covers Seattle, and the role is a full-time position.

Base salary: $250,000–$350,000 USD per year, plus potential equity and benefits.

Company

hirify.global develops AI data infrastructure and full-stack technologies for reliable AI systems used by enterprises, governments, generative AI, defense, and autonomous vehicle applications.

What you will do

• Move across training and fine-tuning, inference, memory and retrieval, evaluation, observability, orchestration, tool use, and applied agent research.
• Research and prototype agent performance improvements, including continuous learning loops, automated data generation, online and offline reinforcement learning, and novel agent architectures.
• Build production AI agents, training pipelines, evaluation systems, infrastructure, and internal tools that reduce experimentation and data bottlenecks.
• Partner with ML and software engineers, product managers, customers, data annotators, and Forward Deployed Engineers to turn research into robust production capabilities.
• Set AI/ML technical direction, define methods and architectures, mentor engineers and scientists, and improve experimental standards across teams.

Requirements

• 5+ years of experience as an ML engineer or applied/research scientist, including training or fine-tuning models in production.
• PhD in Computer Science, Electrical Engineering, or a related field.
• Hands-on experience across model training and fine-tuning, SFT, RLHF/RLAIF, reward modeling, evaluation and observability infrastructure, tool use, planning, memory, and multi-agent orchestration.
• Ability to move across unfamiliar ML problem areas and productionize research by writing and shipping code.
• Experience setting technical direction, collaborating across functions, mentoring engineers and scientists, and influencing standards beyond one team.
• Work location: United States locations listed in the posting.

Nice to have

• Published research, open-source contributions, or patents in agent training, LLM alignment, or applied ML.
• Experience with online learning, continuous fine-tuning, or automated data and curriculum generation from production traces.
• Experience optimizing training efficiency, latency, cost, or inference efficiency at hirify.global.
• Experience in regulated, enterprise, or government environments.
• Experience taking novel training methods or agent architectures from prototype to reliable production systems.

Culture & Benefits

• Health, dental, and vision coverage.
• Retirement benefits, learning and development stipend, and generous paid time off.
• Potential commuter stipend and equity compensation for eligible roles.
• Inclusive equal opportunity workplace with reasonable accommodation support.